Abstract

<div class="section abstract"><div class="htmlview paragraph">The performance of autonomous vehicle (AV) sensors, such as lidars or cameras, is often hindered during rain. Rain droplets on the AV sensors can cause beam attenuation and backscattering, which in turn causes inaccurate sensor readings and misjudgment by AV algorithms. Most AV systems are equipped with cleaning systems to remove contaminants, such as rain, from AV sensors. One such mechanism is to blow high-speed air over the AV sensors. However, the cleaning air can be hindered by incoming headwind, especially at higher vehicle speeds. An innovative idea proposed here is to use a visor to improve the cleaning performance of AV cleaning systems at higher vehicle speeds. The effectiveness of a baseline visor design was studied using computational fluid dynamics (CFD) air flow analysis and Lagrangian rain droplet tracking. The baseline visor improved the AV sensor cleaning performance in two ways. First, the visor protects the cleaning air flow from being disturbed by headwind. And second, it deflects incoming rain droplets from landing on the sensor. Further visor design exploration and optimization was performed to find designs that do not block the lidar field of view (FOV) while optimizing lidar cleaning performance. One hundred designs were explored using the STAR-CCM+ design exploration tool, and the best designs showed that they can completely deflect incoming headwind at high vehicle speeds while not obstructing the FOV. Therefore, a visor can be a key feature to improve AV sensor rain management.</div></div>

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